November 2022 arXiv papers — page 136

Stephan Held, Yannik Kyle Dustin Spitzley

In this paper, we consider the Uniform Cost-Distance Steiner Tree Problem in metric spaces, a generalization of the well-known Steiner tree problem. Cost-distance Steiner trees minimize the sum of the total length and the weighted path lengths from a dedicated root to the other terminals, which have a weight to penalize the path length. They are applied when

Ehsan Sabouni, Christos G. Cassandras

We consider the problem of a single Autonomous Vehicle (AV) merging into traffic consisting only of Human Driven Vehicles (HDVs) with the goal of minimizing both the travel time and energy consumption of the entire group of vehicles involved in the merging process. This is done by controlling only the AV and determining both the optimal merging sequence and

M. Roueinfar, M. H. Kahaei

A major threat to satellites is space debris with their low mass and high rotational speed. Accordingly, the short observation time of these objects is a major limitation in space research for appropriate detection and decision. As a result, these objects do not fully illuminated, leading to their incomplete images at any snapshot. In this paper, we propose

Yuchen Wu, Kangjie Zhou

Tensor decomposition serves as a powerful primitive in statistics and machine learning, and has numerous applications in problems such as learning latent variable models or mixture of Gaussians. In this paper, we focus on using power iteration to decompose an overcomplete random tensor. Past work studying the properties of tensor power iteration either requi

Chia-Fu Liu, Ali Mostafavi

Community recovery from hazards and crises occurs through various diffusion processes within social and spatial networks of communities. Existing knowledge regarding the diffusion of recovery in community socio-spatial networks, however, is rather limited. To bridge this gap, in this study, we created a network diffusion model to characterize the unfolding o

Nan Wang, Yuval Dagan

This study presents a generalized theory for the diffusion of Brownian particles in shear flows. By solving the Langevin equations using stochastic instead of classical calculus, we propose a new mathematical formulation that resolves the particle MSD at all time scales for any two-dimensional parallel shear flow described by a polynomial velocity profile. W

A. Choplin, S. Goriely, L. Siess

The intermediate neutron capture process (i-process) operates at neutron densities between those of the slow and rapid neutron-capture processes. It can be triggered by the ingestion of protons in a convective helium-burning region. One possible astrophysical site is low-mass low-metallicity asymptotic giant branch (AGB) stars. We study here the possibility

Mehmet Demirtas, Andres Rios-Tascon, Liam McAllister

We provide a user's guide to version 1.0 of the software package CYTools, which we designed to compute the topological data of Calabi-Yau hypersurfaces in toric varieties. CYTools has strong capabilities in analyzing and triangulating polytopes, and can easily handle even the largest polytopes in the Kreuzer-Skarke list. We explain the main functions and the

Paramita Das, Mainak Ghosh, Shamindra Ghosh, Corey Jones

In this paper, we extend Ocneanu's theory of connections on graphs to define a 2-category whose 0-cells are tracial Bratteli diagrams, and whose 1-cells are generalizations of unitary connections. We show that this 2-category admits an embedding into the 2-category of hyperfinite von Neumann algebras, generalizing fundamental results from subfactor theory to

Oleg Asipchuk, Vladyslav Drezels

In this paper, we construct explicit exponential bases on finite or infinite unions of segments of total length one with some conditions on gaps between them. We also construct exponential bases on certain unions of cubes in $\R^d$ and we prove a stability result for unions of segments that generalize Kadec's $\frac{1}{4}-$theorem.

Mrinal Dasgupta, Basem Kamal El-Menoufi, Jack Helliwell

We use a direct QCD approach to carry out the next-to-next-to-leading logarithmic (NNLL) resummation for observables groomed with the modified mass-drop tagger (Soft Drop $\beta=0$). We focus on observables which are additive given an arbitrary number of soft-collinear emissions. For this class of observables, we arrange the structure of the NNLL terms into

Colin Oscar Nancarrow, Yuan Xin

In this work we report on a new bootstrap method for quantum mechanical problems that closely mirrors the setup from conformal field theory (CFT). We use the equations of motion to develop an analogue of the conformal block expansion for matrix elements and impose crossing symmetry in order to place bounds on their values. The method can be applied to any qu

Yue Guo, Wei Qiu, Gondy Leroy, Sheng Wang

Recent lay language generation systems have used Transformer models trained on a parallel corpus to increase health information accessibility. However, the applicability of these models is constrained by the limited size and topical breadth of available corpora. We introduce CELLS, the largest (63k pairs) and broadest-ranging (12 journals) parallel corpus fo

Thomas Vogel, Marc Carwehl, Genaína Nunes Rodrigues, Lars Grunske

Context: The goal of specification pattern catalogs for real-time requirements is to mask the complexity of specifying such requirements in a timed temporal logic for verification. For this purpose, they provide frontends to express and translate pattern-based natural language requirements to formulae in a suitable logic. However, the widely used real-time m

Arnaud Pierens, Richard Nelson

The evolution of circumbinary discs and planets is often studied using two-dimensional (2D) numerical simulations, although recent work suggests that 3D effects may significantly alter the structure of the inner cavity created by the binary. In this study, we present the results of 3D hydrodynamical simulations of circumbinary discs that orbit around analogu

F. Abbate, A. Possenti, A. Ridolfi, V. Venkatraman Krishnan

We present the polarization profiles of 22 pulsars in the globular cluster 47 Tucanae using observations from the MeerKAT radio telescope at UHF-band (544-1088 MHz) and report precise values of dispersion measure (DM) and rotation measure (RM). We use these measurements to investigate the presence of turbulence in electron density and magnetic fields. The st

Tsvi Piran, Raul Jimenez

Minuscule primordial black holes before the end and after inflation can serve as "time capsules" bringing back energy from the past to a later epoch when they evaporate. As these black holes behave like matter, while the rest of the Universe content behaves like radiation, the mass fraction of these black holes, that is tiny at formation, becomes significant

Fabian Bernards, Otfried Gühne

One way to explore multiparticle entanglement is to ask for maximal entanglement with respect to different bipartitions, leading to the notion of absolutely maximally entangled states or perfect tensors. A different path uses unitary invariance and symmetries, resulting in the concept of multiparticle singlet states. We show that these two concepts are incom

Alexandre Adam, Adam Coogan, Nikolay Malkin, Ronan Legin

Inferring accurate posteriors for high-dimensional representations of the brightness of gravitationally-lensed sources is a major challenge, in part due to the difficulties of accurately quantifying the priors. Here, we report the use of a score-based model to encode the prior for the inference of undistorted images of background galaxies. This model is trai

Qinan Wang, Patrick Armstrong, Yossef Zenati, Ryan Ridden-Harper

We present early observations and analysis of the double-peaked Type IIb supernova (SN IIb) 2021zby. $TESS$ captured the prominent early shock cooling peak of SN 2021zby within the first $\sim$10 days after explosion with a 30-minute cadence. We present optical and near-infrared spectral series of SN 2021zby, including three spectra during the shock cooling

Zhong-Zhi Xianyu, Hongyu Zhang

Phenomenological studies of cosmological collider physics in recent years have identified many 1-loop inflation correlators as leading channels for discovering heavy new particles around or above the inflation scale. However, complete analytical results for these massive 1-loop correlators are currently unavailable. In this work, we embark on a program of bo

Harun Acaroğlu, Prateek Agrawal, Monika Blanke

We study a simplified model of lepton-flavoured complex scalar dark matter set up in the Dark Minimal Flavour Violation framework. In this model the Standard Model is extended by a scalar dark matter flavour triplet and a charged fermionic mediator, through which dark matter couples to the right-handed charged leptons of the Standard Model. This interaction

Andac Demir, Baris Coskunuzer, Ignacio Segovia-Dominguez, Yuzhou Chen

In computer-aided drug discovery (CADD), virtual screening (VS) is used for identifying the drug candidates that are most likely to bind to a molecular target in a large library of compounds. Most VS methods to date have focused on using canonical compound representations (e.g., SMILES strings, Morgan fingerprints) or generating alternative fingerprints of t

Shyam Balaji

The Sun emits copious amounts of photons and neutrinos in an approximately spatially isotropic distribution. Diffuse $\gamma$-rays and ultra-high energy (UHE) neutrinos from extragalactic sources may subsequently interact and annihilate with the emitted solar photons and neutrinos respectively. This will in turn induce an anisotropy in the cosmic ray (CR) ba

Torben Skrzypek

We elaborate on the treatment of orbifolds of type IIB string theory on $AdS_5\times S^5$ and their dual gauge theories with integrability techniques. The implementation of orbifolds via twisted spin-chains, thermodynamic Bethe Ansatz equations with chemical potentials and $Y$- and $T$-systems with modified asymptotics is confronted with twisted boundary con

Adolfo Holguin, Wayne W. Weng

We study correlation functions of two AdS giant gravitons in AdS$_5\times S^5$ and a BPS supergravity mode using holography. In the gauge theory these are described by BPS correlators of Schur polynomials of fully-symmetric representations and a single trace operator. We find full agreement between the semiclassical gravity and gauge theory computations at l

Avital Dery, Mitrajyoti Ghosh, Yuval Grossman, Teppei Kitahara

We find that the phase appearing in the unitarity relation between $\mathcal{B}(K_L\rightarrow \mu^+\mu^-)$ and $\mathcal{B}(K_L\rightarrow \gamma\gamma)$ is equal to the phase shift in the interference term of the time-dependent $K\rightarrow \mu^+\mu^-$ decay. A probe of this relation at future kaon facilities constitutes a Standard Model test with a theor

Jack Y. Araz, Michael Spannowsky

The Hamiltonian of an isolated quantum mechanical system determines its dynamics and physical behaviour. This study investigates the possibility of learning and utilising a system's Hamiltonian and its variational thermal state estimation for data analysis techniques. For this purpose, we employ the method of Quantum Hamiltonian-based models for the generati

Sheng-Jie Huang, Jiabin Yu, Rui-Xing Zhang

Topological band theory predicts a $\mathbb{Z}$ classification of three-dimensional (3D) Dirac semimetals (DSMs) at the single-particle level. Namely, an arbitrary number of identical bulk Dirac nodes will always remain locally stable and gapless in the single-particle band spectrum, as long as the protecting symmetry is preserved. In this work, we find that

J. M. M. Neustadt, J. T. Hinkle, C. S. Kochanek, M. T. Reynolds

NGC 5273 is a known optical and X-ray variable AGN. We analyze new and archival IR, optical, UV, and X-ray data in order to characterize its long-term variability from 2000 to 2022. At least one optical changing-look event occurred between 2011 and 2014, when the AGN changed from a Type 1.8/1.9 Seyfert to a Type 1. It then faded considerably at all wavelengt

Brivael Laloux, Antonis Georgakakis, Carolina Andonie, David M. Alexander

A complete census of Active Galactic Nuclei (AGN) is a prerequisite for understanding the growth of supermassive black holes across cosmic time. A significant challenge toward this goal is the whereabouts of heavily obscured AGN that remain uncertain. This paper sets new constraints on the demographics of this population by developing a methodology that comb

Alessio Notari, Fabrizio Rompineve, Giovanni Villadoro

We strengthen the cosmological bound on the axion mass, by solving the momentum-dependent Boltzmann equations for axion-pion scatterings and by using a phenomenological production rate derived from pion-pion scattering data, overcoming the breakdown of chiral perturbation theory. Using present cosmological datasets we obtain $m_a\leq 0.24~\text{eV}$. To furt

Tyler D. Ellison, Yu-An Chen, Arpit Dua, Wilbur Shirley

We construct Pauli topological subsystem codes characterized by arbitrary two-dimensional Abelian anyon theories--this includes anyon theories with degenerate braiding relations and those without a gapped boundary to the vacuum. Our work both extends the classification of two-dimensional Pauli topological subsystem codes to systems of composite-dimensional q

Arturo de Giorgi, Luca Merlo, Stefan Pokorski

The recent CDF-II measurement of the $W$-boson mass shows a strong tension with the corresponding Standard Model prediction. Once active neutrino masses are explained in the context of the Low-Scale Seesaw mechanisms, this tension can be resolved. We investigate the possibility of explaining the longstanding muon anomalous magnetic moment anomaly within the

Michael J. Smith, James E. Geach

In this review, we explore the historical development and future prospects of artificial intelligence (AI) and deep learning in astronomy. We trace the evolution of connectionism in astronomy through its three waves, from the early use of multilayer perceptrons, to the rise of convolutional and recurrent neural networks, and finally to the current era of uns

Jan D. Burger, Jesús Zavala, Laura V. Sales, Mark Vogelsberger

Impulsive supernova feedback and non-standard dark matter models, such as self-interacting dark matter (SIDM), are the two main contenders for the role of the dominant core formation mechanism at the dwarf galaxy scale. Here we show that the impulsive supernova cycles that follow episodes of bursty star formation leave distinct features in the distribution f

Yifan Chen, Xiao Xue, Richard Brito, Vitor Cardoso

Gravitational atoms produced from the superradiant extraction of rotational energy of spinning black holes can reach energy densities significantly higher than that of dark matter, turning black holes into powerful potential detectors for ultralight bosons. These structures are formed by coherently oscillating bosons, which induce oscillating metric perturba

Noah Sailer, Simone Ferraro, Emmanuel Schaan

Extragalactic foregrounds are known to generate significant biases in temperature-based CMB lensing reconstruction. Several techniques, which include ``source hardening'' and ``shear-only estimators'' have been proposed to mitigate contamination and have been shown to be very effective at reducing foreground-induced biases. Here we extend both techniques to

Antonio Loquercio, Ashish Kumar, Jitendra Malik

In this work, we show how to learn a visual walking policy that only uses a monocular RGB camera and proprioception. Since simulating RGB is hard, we necessarily have to learn vision in the real world. We start with a blind walking policy trained in simulation. This policy can traverse some terrains in the real world but often struggles since it lacks knowle

Tristan C. Collins, Sebastien Picard, Shing-Tung Yau

We study the Strominger system with fixed balanced class. We show that classes which are the square of a K\"ahler metric admit solutions to the system for vector bundles satisfying the necessary conditions. Solutions are constructed by deforming a Calabi-Yau metric and a Hermitian-Yang-Mills metric along a path inside the given cohomology class.

Arman Rahmim, Tyler J. Bradshaw, Irène Buvat, Joyita Dutta

The SNMMI Artificial Intelligence (SNMMI-AI) Summit, organized by the SNMMI AI Task Force, took place in Bethesda, MD on March 21-22, 2022. It brought together various community members and stakeholders from academia, healthcare, industry, patient representatives, and government (NIH, FDA), and considered various key themes to envision and facilitate a brigh

Vivien Cabannes, Alberto Bietti, Randall Balestriero

Unsupervised representation learning aims at describing raw data efficiently to solve various downstream tasks. It has been approached with many techniques, such as manifold learning, diffusion maps, or more recently self-supervised learning. Those techniques are arguably all based on the underlying assumption that target functions, associated with future do

Duo Xu, Stella S. R. Offner, Robert Gutermuth, Jonathan C. Tan

We define a sample of 200 protostellar outflows showing blue and redshifted CO emission in the nearby molecular clouds Ophiuchus, Taurus, Perseus and Orion to investigate the correlation between outflow orientations and local, but relatively large-scale, magnetic field directions traced by Planck 353 GHz dust polarization. At high significance (p~1e-4), we e

Aftab Ali, Muhammad Usman

We introduce $\delta$ type vertex conditions for beam operators, the fourth derivative operator, on metric graphs and study the effect of certain geometrical alterations (graph surgery) of the graph on the spectra of beam operators on compact metric graphs. Results are obtained for a class of vertex conditions which can be seen as an analogue of {\delta} ver

Maitreya Patel, Tejas Gokhale, Chitta Baral, Yezhou Yang

Videos often capture objects, their visible properties, their motion, and the interactions between different objects. Objects also have physical properties such as mass, which the imaging pipeline is unable to directly capture. However, these properties can be estimated by utilizing cues from relative object motion and the dynamics introduced by collisions.

Xin Lu, Dai-Wei Qu, Yang Qi, Wei Li

Inspired by the observation of a robust $d$-wave superconducting phase driven by tuning the next-nearest-neighbor (NNN) electron hopping in recent density matrix renormalization group (DMRG) studies of six- and eight-leg $t$-$J$ model, we systematically study the phase diagram of the two-leg $t$-$J$ ladder with the NNN couplings (including NNN hopping and sp

Laurens Lootens, Clement Delcamp, Frank Verstraete

It has been a long-standing open problem to construct a general framework for relating the spectra of dual theories to each other. Here, we solve this problem for the case of one-dimensional quantum lattice models with symmetry-twisted boundary conditions. In ref. [PRX Quantum 4, 020357], dualities are defined between (categorically) symmetric models that on

Sheng Sun, Morris Repeta, Mike Healy, Vish Nandall

5G is destined to be supporting large deployment of Industrial IoT (IIoT) with the characteristics of ultra-high densification and low latency. 5G utilizes a more intelligent architecture, with Radio Access Networks (RANs) no longer constrained by base station proximity or proprietary infrastructure. The 3rd Generation Partnership Project (3GPP) covers telec

C. Reichhardt, Ido Regev, K. Dahmen, S. Okuma

Reversible to irreversible (R-IR) transitions arise in numerous periodically driven collectively interacting systems that, after a certain number of driving cycles, organize into a reversible state where the particle trajectories repeat, or remain irreversible with chaotic motion. R-IR transitions were first systematically studied for periodically sheared di

Isabel K. Darcy, Garrett Jones, Puttipong Pongtanapaisan

Although rare, an increasing number of proteins have been observed to contain entanglements in their native structures. To gain more insight into the significance of protein knotting, researchers have been investigating protein knot formation using both experimental and theoretical methods. Motivated by the hypothesized folding pathway of $\alpha$-haloacid d

Zijing Zhang, Jianlin Zhou, Thomas B. Conroy, Samuel Chung

Objective: Dyspnea is one of the most common symptoms for many pulmonary diseases including COVID-19. Clinical assessment of dyspnea is mainly performed by subjective self-report, which has limited accuracy and is challenging for continuous monitoring. The objective of this research study is to determine if dyspnea progression in COVID patients can be assess

J. D. R. Pierel, N. Arendse, S. Ertl, X. Huang

Supernovae (SNe) that have been multiply-imaged by gravitational lensing are rare and powerful probes for cosmology. Each detection is an opportunity to develop the critical tools and methodologies needed as the sample of lensed SNe increases by orders of magnitude with the upcoming Vera C. Rubin Observatory and Nancy Grace Roman Space Telescope. The latest

Ulises Botija-Munoz, Chenggui Yuan

In this paper we investigate explicit numerical approximations for stochastic differential delay equations (SDDEs) under a local Lipschitz condition by employing the adaptive Euler-Maruyama (EM) method. Working in both finite and infinite horizons, we achieve strong convergence results by showing the boundedness of the pth moments of the adaptive EM solution

Ankit Aggarwal, Alejandra Castro, Stéphane Detournay, Beatrix Mühlmann

Warped conformal field theories (WCFTs) are two-dimensional non-relativistic systems, with a chiral scaling and shift symmetry. We present a detailed derivation of the near-extremal limit for their torus partition function. This limit requires large values of the central charge, and is only consistent for non-unitary WCFT. We compare our analysis with previo

Li-Cheng Lan, Huan Zhang, Ti-Rong Wu, Meng-Yu Tsai

The success of AlphaZero (AZ) has demonstrated that neural-network-based Go AIs can surpass human performance by a large margin. Given that the state space of Go is extremely large and a human player can play the game from any legal state, we ask whether adversarial states exist for Go AIs that may lead them to play surprisingly wrong actions. In this paper,

Jeremy Booher, Sean Cotner, Shiang Tang

In this paper we study the universal lifting spaces of local Galois representations valued in arbitrary reductive group schemes when $\ell \neq p$. In particular, under certain technical conditions applicable to any root datum we construct a canonical smooth component in such spaces, generalizing the minimally ramified deformation condition previously studie

Zijing Zhang, Edwin C. Kan

Conventional electromyography (EMG) measures the continuous neural activity during muscle contraction, but lacks explicit quantification of the actual contraction. Mechanomyography (MMG) and accelerometers only measure body surface motion, while ultrasound, CT-scan and MRI are restricted to in-clinic snapshots. Here we propose a novel radiomyography (RMG) fo

Robert Wilms

We introduce the notion of $\epsilon$-irreducibility for arithmetic cycles meaning that the degree of its analytic part is small compared to the degree of its irreducible classical part. We will show that for every $\epsilon>0$ any sufficiently high tensor power of an arithmetically ample hermitian line bundle can be represented by an $\epsilon$-irreducible

Wayne A. Johnson

Consider a hierarchical log-linear model, given by a simplicial complex, $\Gamma$, and integer matrix $A_\Gamma$. We give a new characterization of the rank of $A_\Gamma$ given by a logarithmic transformation on the exponential Hilbert series of $\Gamma$. We show that, if each random variable in $X$ has the same number of possible outcomes, then this formula

Lotta Jokiniemi, Beatriz Romeo, Catharina Brase, Jenni Kotila

We calculate the nuclear matrix element for the two-neutrino $\beta\beta$ decay of $^{136}$Xe into the first excited $0^+$ state of $^{136}$Ba. We use different many-body methods: the quasiparticle random-phase approximation (QRPA) framework, the nuclear shell model, the interacting boson model (IBM-2), and an effective field theory (EFT) for $\beta$ and $\b

Bokgyeong Kang, Sandra Goldlust, Elizabeth C. Lee, John Hughes

Parental refusal and delay of childhood vaccination has increased in recent years in the United States. This phenomenon challenges maintenance of herd immunity and increases the risk of outbreaks of vaccine-preventable diseases. We examine US county-level vaccine refusal for patients under five years of age collected during the period 2012--2015 from an admi

Piotr Banasinski, Wlodek Bednarek

There is an increasing number of observational evidence that very high energy gamma-rays in radio-loud active galactic nuclei are produced in the direct vicinity of a supermassive black hole (SMBH), close to the base of a relativistic jet. In the case of some blazars, the angle between the jet axis and the observer's line of sight is smaller than the angular

Rafael Frongillo, Dhamma Kimpara, Bo Waggoner

We initiate the study of proper losses for evaluating generative models in the discrete setting. Unlike traditional proper losses, we treat both the generative model and the target distribution as black-boxes, only assuming ability to draw i.i.d. samples. We define a loss to be black-box proper if the generative distribution that minimizes expected loss is e

Marco Cirant, Alessandro Goffi, Tommaso Leonori

This paper studies global a priori gradient estimates for divergence-type equations patterned over the $p$-Laplacian with first-order terms having polynomial growth with respect to the gradient, under suitable integrability assumptions on the source term of the equation. The results apply to elliptic problems with unbounded data in Lebesgue spaces complement

Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak

Machine learning models that convert user-written text descriptions into images are now widely available online and used by millions of users to generate millions of images a day. We investigate the potential for these models to amplify dangerous and complex stereotypes. We find a broad range of ordinary prompts produce stereotypes, including prompts simply

Jayadev Acharya, Yuhan Liu, Ziteng Sun

We study discrete distribution estimation under user-level local differential privacy (LDP). In user-level $\varepsilon$-LDP, each user has $m\ge1$ samples and the privacy of all $m$ samples must be preserved simultaneously. We resolve the following dilemma: While on the one hand having more samples per user should provide more information about the underlyi

Vasyl Pihur

Snapchat, like many other social platforms, provides mechanisms for its users to report content and private/public interactions that violate their sense of safety and decency. From our experience and common sense, we can safely assume that not everybody makes an effort to report, leaving potentially a large number of offending users and content unnoticed. Th

Charilaos Efthymiou

We present novel results for fast mixing of Glauber dynamics using the newly introduced and powerful Spectral Independence method from [Anari, Liu, Oveis-Gharan: FOCS 2020]. In our results, the parameters of the Gibbs distribution are expressed in terms of the spectral radius of the adjacency matrix of $G$, or that of the Hashimoto non-backtracking matrix. T

Dmytro Polishchuk, Han Gardeniers

We design and demonstrate a compact, robust and simple to assemble and tune permanent magnet suitable for NMR relaxometry measurements of microfluidic flows. Soft-magnetic stainless steel plates, incorporated inside the magnet airgap, are key for obtaining substantially improved and tunable field homogeneity. The design is scalable for different NMR probe si

Daniel LeJeune, Pratik Patil, Hamid Javadi, Richard G. Baraniuk

We take a random matrix theory approach to random sketching and show an asymptotic first-order equivalence of the regularized sketched pseudoinverse of a positive semidefinite matrix to a certain evaluation of the resolvent of the same matrix. We focus on real-valued regularization and extend previous results on an asymptotic equivalence of random matrices t

Prathyusha S Nair, Ronald Benjamin

We study the transport of an overdamped Brownian particle in a tilted rough potential driven by a gaussian white noise.We conisder various forms of rough potentials to analyse the effect of roughness on the diffusion and current generated.The variation of current, diffusion coefficient, and peclet number with the static tilting force, amplitude of roughness

Bojan Basrak, Marina Dajaković

We prove several forms of renewal theorem tailored to renewal processes with marks and clusters. In particular, for an i.i.d. sequence $(\xi_i,X_i)_{i \geq 0}$, where $\xi_0$ denotes a finite point process on $\mathbb{R}$ and $X_0$ denotes a nonnegative random variable of finite mean, we consider the renewal sequence $T_i = X_0+\cdots + X_i$, $i \geq 0$, and

Brenden W. Hamilton, Timothy C. Germann

Atomistic and continuum scale modeling efforts have shown that shock induced collapse of porosity can occur via a wide range of mechanisms dependent on pore morphology, shockwave pressure, and material properties. The mechanisms that occur under weaker shocks tend to be more efficient at localizing thermal energy, but do not result in high, absolute temperat

Bingjie Wang, Joel Leja, Ashley Villar, Joshua S. Speagle

Upcoming astronomical surveys will observe billions of galaxies across cosmic time, providing a unique opportunity to map the many pathways of galaxy assembly to an incredibly high resolution. However, the huge amount of data also poses an immediate computational challenge: current tools for inferring parameters from the light of galaxies take $\gtrsim 10$ h

Agustin Besteiro

We consider Complex Ginzburg-Landau equations with a polynomial nonlinearity in the real line. We use splitting-methods to prove well-posedness for a subset of almost periodic spaces. Specifically, we prove that if the initial condition has multiples of an irrational phase, then the solution of the equation maintains those same phases.

Daniel Ketover

We show that the number of genus $g$ embedded minimal surfaces in $\mathbb{S}^3$ tends to infinity as $g\rightarrow\infty$. The surfaces we construct resemble doublings of the Clifford torus with curvature blowing up along torus knots as $g\rightarrow\infty$, and arise from a two-parameter min-max scheme in lens spaces. More generally, by stabilizing and fli

Gunnar S. Bali, Sara Collins, Peter Georg, Daniel Jenkins

We determine the light baryon spectrum on ensembles generated by the Coordinated Lattice Simulations (CLS) effort, employing $N_f=2+1$ flavours of non-perturbatively improved Wilson fermions. The hadron masses are interpolated and extrapolated within the quark mass plane, utilizing three distinct trajectories, two of which intersect close to the physical qua

John A. Baldwin, Steven Sivek

We give new proofs that Khovanov homology detects the figure eight knot and the cinquefoils, and that HOMFLY homology detects $5_2$ and each of the $P(-3,3,2n+1)$ pretzel knots. For all but the figure eight these mostly follow the same lines as in previous work. The key difference is that in honor of Tom Mrowka's 60th birthday, the arguments here use instant

Ashwani Bhat, Ashutosh Modi

Predicting emotions expressed in text is a well-studied problem in the NLP community. Recently there has been active research in extracting the cause of an emotion expressed in text. Most of the previous work has done causal emotion entailment in documents. In this work, we propose neural models to extract emotion cause span and entailment in conversations.

Louis Leconte, Sholom Schechtman, Eric Moulines

In this paper, we develop a new algorithm, Annealed Skewed SGD - AskewSGD - for training deep neural networks (DNNs) with quantized weights. First, we formulate the training of quantized neural networks (QNNs) as a smoothed sequence of interval-constrained optimization problems. Then, we propose a new first-order stochastic method, AskewSGD, to solve each co

Serena Federico, Zongyuan Li, Xueying Yu

We prove unique continuation properties for linear variable coefficient Schr\"odinger equations with bounded real potentials. Under certain smallness conditions on the leading coefficients, we prove that solutions decaying faster than any cubic exponential rate at two different times must be identically zero. Assuming a transversally anisotropic type conditi

Bruno de Mendonça Braga, Joseph Eisner, David Sherman

We consider operators on $L^2$ spaces that expand the support of vectors in a manner controlled by some constraint function. The primary objects of study are $\mathrm C^*$-algebras that arise from suitable families of constraints, which we call support expansion $\mathrm C^*$-algebras. In the discrete setting, support expansion $\mathrm C^*$-algebras are cla

R. Debnath, A. Negi, S. AC, K. S. Kamath

During the last century many observations have been made to peep into the dark matter in the universe and many astonishing behaviors of Galaxy clusters have been found which do not fit to any theories formulated before. However, Optical Spectroscopic observation has been initially used to measure the rotational velocity of the Andromeda Galaxy as a function

Xiaoyu Liu, Hae-Young Kee

Recently, honeycomb cobaltates with 3$d^7$ were proposed to display Kitaev physics despite weak spin-orbit coupling. However, other theoretical and experimental works found leading XXZ Heisenberg and negligible Kitaev interactions in BaCo$_2$(AsO$_4$)$_2$ (BCAO), which calls for a further study to clarify the origin of the discrepancies. Here we derive the a

Yuhong Fan

We present a magnetohydrodynamic (MHD) simulation of the coronal mass ejection (CME) on 13 December 2006 in the emerging delta-sunspot active region 10930, improving upon a previous simulation by Fan (2016) as follows. (1) Incorporate an ambient solar wind instead of using a static potential magnetic field extrapolation as the initial state. (2) In addition

Tadahiro Oh, Leonardo Tolomeo, Yuzhao Wang, Guangqu Zheng

We study the hyperbolic $\Phi^{k+1}_2$-model on the plane. By establishing coming down from infinity for the associated stochastic nonlinear heat equation (SNLH) on the plane, we first construct a $\Phi^{k+1}_2$-measure on the plane as a limit of the $\Phi^{k+1}_2$-measures on large tori. We then study the canonical stochastic quantization of the $\Phi^{k+1}

MicroBooNE collaboration, P. Abratenko, D. Andrade Aldana, L. Arellano

We present the first measurement of differential cross sections for charged-current muon neutrino interactions on argon with one muon, two protons, and no pions in the final state. These final states are dominated by two-nucleon knockout interactions, which are complicated to model and for which there is currently limited information about the characteristic

Han Pyo Lee, Yiyan Li, Lidong Song, Di Wu

This paper presents a novel Iterative Bidirectional Gradient Boosting Model (IBi-GBM) for estimating the baseline of Conservation Voltage Reduction (CVR) programs. In contrast to many existing methods, we treat CVR baseline estimation as a missing data retrieval problem. The approach involves dividing the load and its corresponding temperature profiles into

Omanshu Thapliyal, Inseok Hwang

In this paper, we present a data-driven framework for real-time estimation of reachable sets for control systems where the plant is modeled using neural networks (NNs). We utilize a running example of a quadrotor model that is learned using trajectory data via NNs. The NN learned offline, can be excited online to obtain linear approximations for reachability

Shu-Jie Cao, Ritesh Goenka, Chau-Wai Wong, Ajit Rajwade

Group testing can help maintain a widespread testing program using fewer resources amid a pandemic. In a group testing setup, we are given n samples, one per individual. Each individual is either infected or uninfected. These samples are arranged into m < n pooled samples, where each pool is obtained by mixing a subset of the n individual samples. Infected i

Mehedi Hasan Bijoy, Nahid Hossain, Salekul Islam, Swakkhar Shatabda

Spelling error correction is the task of identifying and rectifying misspelled words in texts. It is a potential and active research topic in Natural Language Processing because of numerous applications in human language understanding. The phonetically or visually similar yet semantically distinct characters make it an arduous task in any language. Earlier e

Sergio L. Cacciatori, Pierpaolo Mastrolia

By elaborating on the recent progress made in the area of Feynman integrals, we apply the intersection theory for twisted de Rham cohomologies to simple integrals involving orthogonal polynomials, matrix elements of operators in Quantum Mechanics and Green's functions in Field Theory, showing that the algebraic identities they obey are related to the decompo

Chenghan Li, Junjie Yang, Xing Zhang, Garnet Kin-Lic Chan

The practical description of disordered chemical reactions, where reactions involve multiple species at multiple sites, is presently challenge using correlated electronic structure methods. Here we describe the gradient theory of multi-fragment density matrix embedding theory, which potentially provides a minimal computational framework to model such process

A. V. Lipatov, G. I. Lykasov, M. A. Malyshev

We propose a new analytical expression for the Transverse Momentum Dependent (TMD, or unintegrated) gluon density in the proton. Essential phenomenological parameters are extracted from the LHC data on inclusive hadron production in $pp$ collisions at low transverse momenta, $p_T \sim 1$~GeV. The latter are described in the framework of modified soft quark-g

Carl Doersch, Ankush Gupta, Larisa Markeeva, Adrià Recasens

Generic motion understanding from video involves not only tracking objects, but also perceiving how their surfaces deform and move. This information is useful to make inferences about 3D shape, physical properties and object interactions. While the problem of tracking arbitrary physical points on surfaces over longer video clips has received some attention,

Guillaume Cecile, Sarang Gopalakrishnan, Romain Vasseur, Jacopo De Nardis

Motivated by recent cold atom experiments, we study the relaxation of spin helices in quantum XXZ spin chains. The experimentally observed relaxation of spin helices follows scaling laws that are qualitatively different from linear-response transport. We construct a theory of the relaxation of helices, combining generalized hydrodynamics (GHD) with diffusive

Valentin Buciumas, Manish M. Patnaik

We describe the structure of the Whittaker or Gelfand-Graev module on a $n$-fold metaplectic cover of a $p$-adic group $G$ at both the Iwahori and spherical level. We express our answer in terms of the representation theory of a quantum group at a root of unity attached to the Langlands dual group of $G$. To do so, we introduce an algebro-combinatorial model

M. Gidding, T. Janssen, C. S. Davies, A. Kirilyuk

Nonlinear dynamics can give rise, via the processes of self-organisation and pattern formation, to the spontaneous manifestation of order in open and complex systems far from equilibrium. Self-organising systems, transforming the inflow of energy into information, are ubiquitously found in current topical areas of science ranging from brainwave entrainment a

Ashay Burungale, Kâzım Büyükboduk, Antonio Lei

Let $p\ge 5$ be a prime number, $E/\mathbb{Q}$ an elliptic curve with good supersingular reduction at $p$ and $K$ an imaginary quadratic field such that the root number of $E$ over $K$ is $+1$. When $p$ is split in $K$, Darmon and Iovita formulated the plus and minus Iwasawa main conjectures for $E$ over the anticyclotomic $\mathbb{Z}_p$-extension of $K$, an

Yashesh Gaur, Nick Kibre, Jian Xue, Kangyuan Shu

Automatic Speech Recognition (ASR) systems typically yield output in lexical form. However, humans prefer a written form output. To bridge this gap, ASR systems usually employ Inverse Text Normalization (ITN). In previous works, Weighted Finite State Transducers (WFST) have been employed to do ITN. WFSTs are nicely suited to this task but their size and run-